Power Generation Equipment and Process Data

Common Types

• Turbine vibration monitoring (rotor imbalance, misalignment)
• Bearing temperature sensors
• Oil Condition and particulate analysis
• Generator electrical output (voltage, frequency, load)

Uncommon/Advanced Types

• Blade tip timing sensors for real-time turbine blade stress analysis
• Acoustic emission monitoring for crack detection
• Infrared thermography of high-voltage equipment
• Real-time efficiency mapping across load profiles

Possible Insights

• Predictive maintenance to avoid catastrophic turbine failure
• Optimizing fuel efficiency and power output curves
• Detecting early stage mechanical or electrical faults before shutdowns

Renewable Energy Asset Data

Common Types

• Solar inverter performance (output, efficiency, fault logs)
• Wind turbine rotational speed and power curves
• Environmental data (wind speed, solar irradiance, temperature)

Uncommon/Advanced Types

• PV module level performance monitoring with thermal imaging
• Blade pitch vibration analysis for wind turbines
• Predictive weather linked output forecasting
• AI driven fault pattern recognition in inverter failure modes

Possible Insights

• Maximizing renewable energy capture based on real time environmental conditions
• Detecting and replacing underperforming panels or turbines quickly
• Extenting component lifespan with proactive adjustments to operating conditions

Electric and Gas Utility Distribution Data

Common Types

• Smart meter readings (electricity, gas)
• Load demand trends
• Substation status and fault alarms
• Transformer oil temperature and load

Uncommon/Advanced Types

• Partial discharge monitoring in transformers
• Gas pipeline acoustic leak detection
• Dynamic grid topology mapping for real-time reconfiguration
• High resolution harmonic distortion monitoring

Possible Insights

• Avoiding blackouts with real-time load balancing
• Detecting hidden losses and thefts in the grid
• Improving asset health through condition based transformer maintenance
• Faster outage detection and restoration

District Heating and Cooling System Data

Common Types

• Supply and return temperatures
• Flow rates in main and branch lines
• Pump and valve status

Uncommon/Advanced Types

• Thermal leak detection along buried distribution lines
• AI driven demand prediction for heating/cooling load
• Energy intensity per building/zone analysis

Possible Insights

• Lower operating costs via optimized load distribution
• Rapid detection of heat/cool loss for reduced waste
• More accurate seasonal capacity planning

Environmental and Regulatory Compliance Data

Common Types

• Stack emissions (NOx, SOx, CO2, particulates)
• Water usage and discharge quantity

Uncommon/Advanced Types

• Real-tie carbon footprint per MWh generated
• AI driven compliance alerts before violations occur
• Satellite or drone based inspection of remote assets

Possible Insights

• Avoiding environmental fines and improving ESG scores
• Demonstrating sustainability progress to regulators and investors
• Lowering carbon intensity through data-driven operational changes